Adaptive Segmentation of MRI Data

Abstract. Intensity-based classification of MR images has proven problematic, even when advanced techniques are used. Intra-scan and interscan intensity inhomogeneities are a common source of difficulty. While reported methods have had some success in correcting intra-scan inhomogeneities, such methods require supervision for the individual scan. This paper describes a new method called adaptive segmentation that uses knowledge of tissue intensity properties and intensity inhomogeneities to correct and segment MR images. Use of the EM algorithm leads to a fully automatic method that allows for more accurate segmentation of tissue types as well as better visualization of MRI data, that has proven to be effective in a study that includes more than 1000 brain scans.

• Type: Conference
• Year: 1995
• Where: CVRMED
• Authors: William M. Wells III, W. Eric L. Grimson, Ron Kikinis, Ferenc A. Jolesz
• Keywords: Computer Vision, CVRMED 1995, Intensity Inhomogeneities, Interscan Intensity Inhomogeneities, MR Images